Mosquitoes, Lymphatic Filariasis, and Public Health: A Systematic Review of Anopheles and Aedes Surveillance Strategies

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Abstract

Lymphatic Filariasis (LF) affects over 120 million people in 72 countries, with sub-periodic filariasis common in the Pacific. Wuchereria bancrofti has three physiological races, each with a unique microfilarial periodicity, and each race is isolated to a specific geographical region. Sub-periodic W. bancrofti is transmitted by various Aedes mosquito species, with Aedes polynesiensis and Aedes samoanus being the primary vectors in Samoa. The Aedes scutellaris and Aedes kochi groups are also important vectors in the South Pacific Islands. Anopheles species are important vectors of filariasis in rural areas of Asia and Africa. The Anopheles gambiae complex, Anopheles funestus, and the Anopheles punctulatus group are the most important vectors of W. bancrofti. These vectors exhibit indoor nocturnal biting behaviour and breed in a variety of habitats, including freshwater, saltwater, and temporary water bodies. Effective vector surveillance is central to LF control and elimination programs. However, the traditional Human Landing Collection (HLC) method, while valuable, poses ethical concerns and risks to collectors. Therefore, this review critically analyses alternative trapping tools for Aedes and Anopheles vectors in LF-endemic regions. We looked at 14 research publications that discussed W. bancrofti vector trapping methods. Pyrethrum Spray Catches (PSC), one of the seven traps studied for Anopheles LF vectors, was revealed to be the second most effective strategy after HLC, successfully catching Anopheles vectors in Nigeria, Ghana, Togo, and Burkina Faso. The PSC method has several drawbacks, such as the likelihood of overlooking exophilic mosquitoes or underestimating Anopheles populations. However, exit traps offered hope for capturing exophilic mosquitoes. Anopheles populations could also be sampled using the Anopheles Gravid Trap (AGT). In contrast, the effectiveness of the Double Net Traps (DNT) and the CDC Light Trap (CDC LT) varied. Gravid mosquito traps like the OviArt Gravid Trap (AGT) were shown to be useful tools for identifying endophilic and exophilic vectors during the exploration of novel collection techniques. The Stealth trap (ST) was suggested for sampling Anopheles mosquitoes, although specimen damage may make it difficult to identify the species. Although it needs more confirmation, the Ifakara Tent Trap C design (ITT-C) showed potential for outdoor mosquito sampling in Tanzania. Furvela tent traps successfully captured a variety of Anopheles species and are appropriate for use in a variety of eco-epidemiological settings. By contrast, for Aedes LF vectors, no specific sampling tool was identified for Aedes niveus, necessitating further research and development. However, traps like the Duplex cone trap, Resting Bucket Trap (RB), and Sticky Resting Bucket trap (SRB) proved effective for sampling Aedes albopictus, offering potential alternatives to HLC. This review emphasises the value of looking into alternative trapping methods for Aedes and Anopheles vectors in the LF-endemic region. Further research is required to determine the efficacy of novel collection techniques in various contexts, even if PSC and AGT show promise for sampling Anopheles vectors. The identified traps, along with ongoing research, provide valuable contributions to vector surveillance efforts in LF-endemic regions, enabling LF control and elimination strategies to advance.

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Incidence of malaria among mosquito collectors conducting human landing catches in western Kenya.

Meghna Desai, John Williamson, Nathalie Hamel … (2013)

The human landing catch (HLC) has long been the gold standard for estimating malaria transmission by mosquitoes, but has come under scrutiny because of ethical concerns of exposing collectors to infectious bites. We estimated the incidence of Plasmodium falciparum malaria infection in a cohort of 152 persons conducting HLCs and compared it with that of 147 non-collectors in western Kenya. Participants were presumptively cleared of malaria with Coartem™ (artemether-lumefantrine) and tested for malaria every 2 weeks for 12 weeks. The HLC collections were conducted four nights per week for six weeks. Collectors were provided chemoprophylaxis with Malarone™ (atovaquone-proguanil) during the six weeks of HLC activities and one week after HLC activities were completed. The incidence of malaria was 96.6% lower in collectors than in non-collectors (hazard ratio = 0.034, P < 0.0001). Therefore, with proper prophylaxis, concern about increased risk of malaria among collectors should not be an impediment to conducting HLC studies.

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A new tent trap for sampling exophagic and endophagic members of the Anopheles gambiae complex

Nicodemus J Govella, Prosper P. Chaki, Yvonne Geissbuhler … (2009)

Background Mosquito sampling methods are essential for monitoring and evaluating malaria vector control interventions. In urban Dar es Salaam, human landing catch (HLC) is the only method sufficiently sensitive for monitoring malaria-transmitting Anopheles. HLC is labour intensive, cumbersome, hazardous, and requires such intense supervision that is difficulty to sustain on large scales. Methods Novel tent traps were developed as alternatives to HLC. The Furvela tent, designed in Mozambique, incorporates a CDC Light trap (LT) components, while two others from Ifakara, Tanzania (designs A and B) require no electricity or moving parts. Their sensitivity for sampling malaria vectors was compared with LT and HLC over a wide range of vector abundances in rural and urban settings in Tanzania, with endophagic and exophagic populations, respectively, using randomised Latin-square and cross- over experimental designs. Results The sensitivity of LTs was greater than HLC while the opposite was true of Ifakara tent traps (crude mean catch of An. gambiae sensu lato relative to HLC = 0.28, 0.65 and 1.30 for designs A, B and LT in a rural setting and 0.32 for design B in an urban setting). However, Ifakara B catches correlated far better to HLC (r2 = 0.73, P < 0.001) than any other method tested (r2 = 0.04, P = 0.426 and r2 = 0.19, P = 0.006 for Ifakara A and LTs respectively). Only Ifakara B in a rural setting with high vector density exhibited constant sampling efficiency relative to HLC. The relative sensitivity of Ifakara B increased as vector densities decreased in the urban setting and exceeded that of HLC at the lowest densities. None of the tent traps differed from HLC in terms of the proportions of parous mosquitoes (P ≥ 0.849) or An. gambiae s.l. sibling species (P ≥ 0.280) they sampled but both Ifakara A and B designs failed to reduce the proportion of blood-fed mosquitoes caught (Odds ratio [95% Confidence Interval] = 1.6 [1.2, 2.1] and 1.0 [0.8, 1.2], P = 0.002 and 0.998, respectively), probably because of operator exposure while emptying the trap each morning. Conclusion The Ifakara B trap may have potential for monitoring and evaluating a variety of endophagic and exophagic Afrotropical malaria vectors, particularly at low but epidemiologically relevant population densities. However, operator exposure to mosquito bites remains a concern so additional modifications or protective measures will be required before this design can be considered for widespread, routine use.

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Transmission Assessment Surveys (TAS) to Define Endpoints for Lymphatic Filariasis Mass Drug Administration: A Multicenter Evaluation

Brian Chu, Michael S. Deming, Nana-Kwadwo Biritwum … (2013)

Introduction Lymphatic filariasis (LF) is a mosquito-borne parasitic disease endemic to 73 countries worldwide. An estimated 1.4 billion people are said to be at-risk of LF disease with approximately 120 million infected and 40 million suffering from the crippling and stigmatizing clinical manifestations of the disease, especially lymphoedema and hydrocele [1]. As such, LF is one of the leading causes of chronic disability worldwide. The primary focus for control and elimination of LF is the interruption of disease transmission through treatment of the entire at-risk population with repeated annual mass drug administration (MDA) using a single-dose combination of albendazole with either diethylcarbamazine (DEC) or ivermectin [2]. Since 2000, these efforts have been coordinated through the World Health Organization's (WHO) Global Programme to Eliminate Lymphatic Filariasis (GPELF), a collaborative public health program that has delivered to date nearly 4 billion drug treatments to over 950 million individuals in 53 countries [1]. This extraordinary achievement, made possible through the drug donations of manufacturers Merck (ivermectin) and GlaxoSmithKline (albendazole) has resulted in a marked reduction of infection prevalence in endemic areas, along with sizeable health and economic benefits to the affected populations [3], [4]. Essential to the Global Programme's success in combating LF is the important challenge of defining and confirming endpoints for MDA when disease transmission is presumed to have reached a level low enough that it cannot be sustained even in the absence of drug intervention. Given the biology and parasitic life cycle of LF, this threshold of infection is most likely to be reached following 4–6 annual MDA rounds with effective population coverage and a resulting microfilaria (mf) prevalence rate 1 so household enumeration was necessary. Following specimen collection, all blood-filled tubes were stored and transported via cold-chain to a nearby laboratory base to process and record ICT (or PanLF, Brugia Rapid) test results. Children testing positive were identified using the EDGE/ODK systems and individually followed up at night during peak mf hours to collect an additional blood sample for mf testing (10pm–2am except in American Samoa where W. bancrofti shows diurnal periodicity). The number of children absent on the survey date was recorded for all surveys. For community surveys, field teams made at least one revisit to the absent child's house before recording an official absence. The number of selected children without consent or refusing to participate was also captured in addition to invalid and incomplete tests due to malfunction or insufficient blood. Together, these absentees, refusals, and individuals with test errors were designated as TAS non-participators. Data Analysis All transmitted data were compiled into a central database at the Task Force for Global Health and exported into Microsoft Excel spreadsheets for final cleaning and approval by the collaborating principal investigators. Statistical analysis was done by importing the clean datasets into SAS v9.3 (SAS Institute). Summary statistics of test results and univariate analyses with regard to age, sex, and location were performed using the PROC UNIVARIATE function. Design effect calculations were conducted using the PROC SURVEYFREQ function. Results TAS Results For W. bancrofti countries , TAS-1 and TAS-2 results are presented in Table 3. All EUs passed TAS-1, meaning that the number of ICT positive children was no greater than the critical cutoff value. As recommended by the TAS, MDA was then stopped (or periodic post-MDA surveillance continued) in those specific EUs for approximately 24 months before conducting TAS-2. All W. bancrofti EUs (with the exception of American Samoa and Indonesia where follow-up assessments were not yet completed) also passed TAS-2, thereby corroborating the TAS-1 stop-MDA or post-MDA surveillance decision. Microfilaraemia (mf) tests were conducted on ICT positive children using the three-line blood smear (TAS-1 and TAS-2) and PCR (TAS-1) procedures. The proportion of mf-positive children among antigen-positive children identified in the TAS was low in the W. bancrofti countries. The positive blood smear to positive ICT proportion was 12.9% (4/31) for TAS-1 and 5.2% (1/19) for TAS-2, while the proportion of positive PCR to positive ICT was 22.6% (7/31). 10.1371/journal.pntd.0002584.t003 Table 3 ICT, blood smear, and PCR results for W. bancrofti countries. ICT (Ag) Blood smear (mf) PCR (mf) Country Critical cutoff value TAS-1 positive1 TAS-2 positive1 TAS-1 positive2 TAS-2 positive2 TAS-1 positive2 Am. Samoa3 6 2/949 n/a 0/2 (0.0%) n/a 0/2 (0.0%) Burkina Faso 18 13/1571 5/1591 2/13 (15.4%) 0/5 (0.0%) 5/13 (38.5%) Dom. Rep. 18 0/1609 3/1558 - 1/3 (33.3%) - Ghana 18 2/1557 0/1514 0/2 (0.0%) - 0/2 (0.0%) Indonesia4 18 6/1312 n/a4 0/6 (0.0%) n/a4 0/6 (0.0%) Philippines 18 2/1599 1/1656 0/2 (0.0%) 0/1 (0.0%) 0/2 (0.0%) Sri Lanka3 8 0/679 1/698 - 0/1 (0.0%) - Togo 18 2/1571 0/1550 1/2 (50.0%) - 1/2 (50.0%) Tanzania 18 10/1561 9/1588 1/10 (10.0%) 0/9 (0.0%) 1/9 (11.1%) Vanuatu 18, 195 0/933 2/954 - 0/2 (0.0%) - 1 % of total survey population. 2 % of ICT+ individuals; some individuals could not be retraced for mf testing. 3 Systematic sampling was used in American Samoa and Sri Lanka. 4 Indonesia EU of Alor+Pantar islands is endemic for both W. bancrofti and Brugia timori. TAS-2 ICT tests were not available due to logistic problems importing diagnostic tests into the country. 5 Census critical cutoff value is equal to .02N for EUs with Culex, Anopheles, or Mansonia as primary LF vector. For Brugia spp. countries, Indonesia passed TAS-1 and TAS-2 and only one mf positive was found across both surveys (Table 4). The number of PanLF positive children in Malaysia (Sabah), however, exceeded the critical cutoff value in TAS-1. MDA was, therefore, continued before re-testing in TAS-2, but for only one round in 8 IUs due to DEC supply problems. Results for TAS-2 using the Brugia Rapid test were still greater than the critical cutoff value so consequently, MDA has been recommended to continue in the EU for two more rounds before conducting another TAS evaluation. Mf results in Malaysia (Sabah, not peninsular Malaysia) confirmed a high likelihood of active transmission with a TAS-1 positive blood smear to positive PanLF proportion of 35.6% (32/90) and positive PCR to positive PanLF proportion of 52.2% (47/90). The TAS-2 positive blood smear to positive Brugia Rapid proportion decreased to 20.5% (15/73) following the additional rounds of MDA. 10.1371/journal.pntd.0002584.t004 Table 4 PanLF, Brugia Rapid, blood smear, and PCR results for Brugia spp. countries. PanLF or Brugia Rapid (Ab) Blood smear (mf) PCR (mf) Country Critical cutoff value TAS-1 (PanLF) positive1 TAS-2 (Brugia Rapid) positive1 TAS-1 positive2 TAS-2 positive2 TAS-1 positive2 Indonesia3 18 12/1353 14/1622 0/12 (0.0%) 1/14 (7.1%) 0/12 (0.0%) Malaysia 16 90/1429 73/1684 31/87 (35.6%) 15/73 (20.5%) 46/86 (53.4%) 1 % of total survey population. 2 % of PanLF(+) or Brugia Rapid(+) individuals; some individuals could not be retraced for mf testing. 3 Indonesia EU of Alor and Pantar islands is endemic for both W. bancrofti and Brugia timori. Population and Sampling Characteristics The proportions of male and female children sampled were very even across all school and community-based surveys in both TAS-1 and TAS-2 (Table 5). In addition, no one country in either survey had more than 54% male or female children in the sample. 10.1371/journal.pntd.0002584.t005 Table 5 TAS sample size by sex for school and community-based surveys. Sex School TAS (16 surveys) Community-based TAS (6 surveys) Total (22 surveys) Male 9,894 (50.2%) 4,752 (50.1%) 14,646 (50.2%) Female 9,798 (49.8%) 4,725 (49.9%) 14,523 (49.8%) Total1 19,692 (100.0%) 9,477 (100.0%) 29,169 (100.0%) 1 57 records were missing sex identification data. The target age group for TAS is 6 and 7 year old children, approximated by 1st and 2nd graders in school surveys. In W. bancrofti EUs, 84% of the total sample in school surveys was aged 6 and 7 and 95% between 6 and 10 years old (Table 6). The Brugia spp. EUs in Indonesia and Malaysia found a higher proportion of 8 year olds in the TAS sample due to 1st and 2nd grade in both countries primarily consisting of 7 and 8 year old children. No positive cases were detected outside the 6–10 year old range although one positive ICT test was associated with a child of unspecified age. 10.1371/journal.pntd.0002584.t006 Table 6 TAS results by age for school surveys in W. bancrofti and Brugia. spp. countries. W. bancrofti countries1 Brugia spp. countries Age (years) n (% of total) ICT+ (% of age) n (% of total) PanLF or Brugia Rapid+ (% of age) 10 37 (0.3%) 0 (0.0%) 2 (0.1%) 0 (0.0%) Total2 14,899 (100.0%) 17 (0.1%) 6,088 (100.0%) 189 (3.1%) 1 Includes TAS-1 ICT tests for Indonesia. 2 73 records were missing age data (including 1 ICT+). Table 7 is informative because it displays the target and actual sample sizes for TAS-1 and TAS-2 along with the number of clusters (schools or EAs) surveyed to achieve the total. The target sample size was mostly met in both surveys with a few notable exceptions. In American Samoa TAS-1, there was insufficient blood to perform the ICT test in a number of collected samples. Likewise in Indonesia TAS-1, ICT and PanLF tests were unavailable at the time of sampling; therefore, they were conducted retroactively using preserved serum and several samples did not have enough quantity to complete the test. For TAS-2 in Malaysia, the actual sample size greatly exceeded the target due to the random selection of several large schools in addition to a lower non-participation rate than initially estimated. 10.1371/journal.pntd.0002584.t007 Table 7 Comparison of target and actual sample sizes and number of clusters. Country Survey Target sample Actual sample1 % difference Original clusters selected Extra clusters needed Am. Samoa TAS-1 1,042 949 −8.9% 262 - TAS-2 - - - - - Burkina Faso TAS-1 1,556 1,571 1.0% 30 1 TAS-2 1,556 1,591 2.2% 30 8 Dom. Rep. TAS-1 1,532 1,609 5.0% 30 8 TAS-2 1,532 1,558 1.7% 40 0 Ghana TAS-1 1,556 1,557 0.1% 30 10 TAS-2 1,556 1,514 −2.7% 30 2 Indonesia TAS-1 1,548 1,353 −12.6% 30 13 TAS-2 1,548 1,622 4.8% 30 0 Malaysia TAS-1 1,368 1,429 4.5% 30 2 TAS-2 1,368 1,684 23.1% 33 0 Philippines TAS-1 1,552 1,599 3.0% 35 10 TAS-2 1,552 1,656 6.7% 35 0 Sri Lanka TAS-1 684 679 −0.7% 352 - TAS-2 684 698 2.0% 322 0 Togo TAS-1 1,548 1,571 1.5% 30 1 TAS-2 1,540 1,550 0.6% 39 0 Tanzania TAS-1 1,540 1,561 1.4% 51 18 TAS-2 1,540 1,588 3.1% 70 0 Vanuatu TAS-1 933 933 0.0% 63 0 TAS-2 954 954 0.0% 63 0 Total TAS-1 14,859 14,811 −0.3% 390 63 TAS-2 13,830 14,415 4.2% 402 10 1 Excluding invalid tests and specimens unable to be tested. 2 Systematic sampling; all eligible primary sampling units surveyed. Table 7 also presents the number of original clusters selected and the number of extra clusters needed to meet the sampling requirements. In TAS-1, a total of 63 extra clusters were required, most prominently in Ghana, Indonesia, Philippines, and Tanzania. In contrast, only 10 total extra clusters were required in TAS-2, primarily as a result of factoring the non- participation rates into the SSB survey design calculation. The non- participation rate includes children – enrolled in first and second grade (for school surveys) or residing in the selected house (for community-based surveys) – absent on the survey date and those refusing to participate or without consent. The rate was a combined 14.0% for TAS-1 and 10.2% for TAS-2 but varied by country and survey (Table 8). Non-participators also include invalid (i.e. malfunctioning) diagnostic tests or samples that were collected but had insufficient quantity or other barriers preventing completion of the test (e.g. blood clotting). These specific non- participation factors accounted for approximately 4% of total TAS-1 and 2% of total TAS-2 samples but were also dependent on country and survey. Some non- participation rates were not tracked or estimated in American Samoa (TAS-1), Burkina Faso (TAS-1), and Sri Lanka (TAS-1). 10.1371/journal.pntd.0002584.t008 Table 8 Non-participation rates observed in TAS-1 and TAS-2. Absent, refused, or no consent Invalid test or Unable to be tested Country Survey site TAS-1 TAS-2 TAS-1 TAS-2 Am. Samoa School - - 16.0% - Burkina Faso Community - 7.5% 0.9% 0.3% Dom. Rep. Community 12.6% 7.2% 0.6% 0.1% Ghana School 15.0% 15.0% 0.1% 2.9% Indonesia School 20.0% 10.0% 18.3% 9.5% Malaysia School 22.9% 20.4% 0.3% 0.5% Philippines School 4.0% 3.0% 4.0% 1.3% Sri Lanka School - 9.3% 0.0% 1.4% Togo School 12.0% 8.0% 0.0% 0.0% Tanzania Community 14.7% 5.7% 0.6% 1.1% Vanuatu School 10.7% 15.7% 0.0% 0.0% Total - 14.0% 10.2% 3.8% 1.9% Design effects for TAS-1 and TAS-2 cluster surveys are listed in Table 9. All W. bancrofti countries had design effects less than the TAS estimated value of 2 (for target populations >2400), indicating the required sample size was not underestimated. Conversely, Indonesia and Malaysia, both Brugia spp. EUs, had design effects larger than 2 that may be associated with the more sensitive detection of antibody versus antigenemia, and with the subsequently larger number of positive cases found, particularly in Malaysia. 10.1371/journal.pntd.0002584.t009 Table 9 Design effects calculated for TAS-1 and TAS-2 cluster surveys. Country TAS-1 TAS-2 Burkina Faso 1.3 0.8 Dom. Rep. - 1.6 Ghana 2.0 - Indonesia 2.5 2.2 Malaysia 7.9 7.0 Philippines 1.0 1.0 Togo 0.9 - Tanzania 1.1 1.1 Time and Costs of These Studies The overall average number of field days required for TAS was 26 in TAS-1 (range: 9–60) and 27 for TAS-2 (range: 12–50), using an average number of 4 field teams (range: 3–6) with 3–4 persons per team (Table 10). School surveys took 24–27 days on average versus 26–33 for community surveys but the overall survey length was highly dependent on country-specific factors including weather, distance, and other logistic delays, particularly in the Philippines, Dominican Republic, Indonesia, and Vanuatu. 10.1371/journal.pntd.0002584.t010 Table 10 Number of field days required to complete TAS-1 and TAS-2. Survey site Country Field days TAS-1 Field days TAS-2 Field teams TAS-1 and TAS-2 School Am. Samoa 9 - 6 Ghana 20 18 4 Indonesia 35 18 6 Malaysia 18 18 5 Philippines 60 50 3 Sri Lanka 26 32 3 Togo 14 12 3 Vanuatu 25 25 4 Average 27 24 4 Community Burkina Faso 19 18 3 Dom. Rep. 57 42 3 Tanzania 22 19 3 Average 33 26 3 All sites Average 26 27 4 The mean and median TAS costs in this operational research study were $25,500 and $24,900 with the largest proportion of costs allocated to personnel (33%) and transportation (24%) (Tables 11 and 12). Community surveys (mean $26,800, median $26,000) required slightly more resources than school surveys (average $24,900, median $23,800). Project cost was moderately correlated to the area of the EU (R2 = .39). It should be noted, however, that all costs referenced here reflect research budgets and objectives including training, foreign consultants, and extra specimen shipment and analysis; carried out for programmatic purposes, costs would be expected to be less. 10.1371/journal.pntd.0002584.t011 Table 11 Total TAS operational research costs for school and community-based surveys. Survey site Low High Mean Median School (n = 8) $16,200 $36,900 $24,900 $23,800 Community (n = 3) $17,500 $36,800 $26,800 $26,000 Total (n = 11) $16,200 $36,900 $25,500 $24,900 10.1371/journal.pntd.0002584.t012 Table 12 Allocation of TAS costs by spending category. Description % of total costs Personnel (per diems) 33% Transportation (fuel, vehicle hire) 24% Diagnostic tests (procurement, shipment, customs) 15% Consumable supplies (e.g. lancets, EDTA tubes) 14% Communication (e.g. printing, mobile phone data) 3% Other (e.g. training, consultants, sensitization, specimen shipment) 11% Total 100% Discussion LF elimination programs require a standardized methodology that is statistically robust and programmatically feasible in order to assure confidence in making stop-MDA and post-MDA surveillance decisions. In this regard, Transmission Assessment Surveys offer a more pragmatic approach than previous WHO guidelines and with 22 implementations of the TAS in 11 countries, this operational research study provides the first report of a large-scale rollout of the TAS at a programmatic level. Indeed, these field experiences in multiple geographic and epidemiological settings have offered a prime opportunity to evaluate the TAS protocol critically and identify both best practices for future implementation and important remaining research gaps. TAS Results and Sampling Strategy Consistent results were seen across TAS-1 and TAS-2. In the 10 EUs that passed TAS-1, the recommended decision to stop MDA was validated in TAS-2, as no resurgence of infection was observed above the critical cutoff value where active transmission is anticipated as likely to occur. This finding is extremely important from a programmatic perspective because if the TAS-2 result had differed from TAS-1, MDA might have needed to be restarted in the EU, which is not only a resource intensive process but one that could be politically and socially undesirable. A final TAS evaluation is recommended in these EUs after another 2–3 years to confirm the absence of reemerging transmission detectable by the TAS. The results were in-line with anticipated outcomes of the TAS survey design and sampling strategy. Design effects for W. bancrofti EUs fell within expected limits, and participant age and sex reflected distributions in the target population. One notable advantage of the TAS protocol is its inclusion of cluster surveys to reduce the number of survey sites and overall sample size. In this study, 8 of 11 countries used a cluster survey design although sampling efficiency differed from TAS-1 to TAS-2. For TAS-1, a total of 63 extra clusters had to be selected and surveyed in addition to the originally planned sample in order to fulfill the target sample size. Such a process proved burdensome to survey planning and resource allotment. In contrast, only 10 extra clusters were needed in TAS-2 to achieve the target objective. This vast improvement in TAS-2 is largely because of factoring in ‘non-participators’ (i.e. absent children and those refusing to participate or without consent) into the initial survey design calculation. Estimates of the non- participation rate, however, might be difficult to obtain or measure during TAS planning, as was the experience in several of the countries in TAS-2. In such cases, a 10–15% estimated non- participation rate can be recommended based on the results from this study (Table 9), although this rate may vary greatly by EU and survey location. Community-based surveys, in particular, may experience a larger non- participation rate than school surveys because of the unreliable availability of eligible children at specific times of the day. The amount of TAS pre-planning and school or community sensitization is also likely to influence non- participation rates considerably. Because the TAS uses a fixed sampling fraction within each cluster, the inclusion of an accurate non- participation rate into the survey design calculation is also necessary to achieve a more accurate sample size. More specifically, underestimating the non- participation rate would result in larger sampling intervals and, therefore, fewer children sampled per cluster than required given the number of clusters selected. Since the TAS presumes an equal probability sample, extra clusters would be needed to make up the sample size difference, as seen most notably in TAS-1. Despite best efforts to reach sample size targets efficiently using non- participation rates and extra clusters, our study found that discrepancies may persist because of outdated population or enrollment estimates, school closures, inclement weather, and other factors including the selection by chance of several large or small outlier schools. Non-participation is also not unprecedented in such types of surveys and because absentees were randomly spread out across clusters, sampling bias was likely not introduced. Furthermore, the inclusion of extra clusters improved sample robustness and reduced intraclass correlation between clusters. Probability proportional to estimated size (PPES) sampling has been investigated but preliminary assessment suggests the uncertainties of actual school size and number of smaller schools with target children below the fixed number needed would increase the average clusters required and likely offset benefits to standardizing the sample size [16]. Strategic approaches to harmonize the target and actual sample size will likely evolve as the TAS is further field tested and evaluated. Several improvements have already been made to the SSB tool including the input of an estimated non- participation rate and the automatic random selection of ‘backup clusters’ to survey in case the target sample size is not initially met. This study also validated the overall utility and convenience of the SSB tool with regards to simply determining the proper survey design, calculating sample sizes and sampling intervals, and randomizing cluster and child selection lists. Future TAS should continue using the SSB tool for survey planning. The TAS protocol identifies 6–7 year old children as the target age group. While no positive cases were found outside the 6–10 year age range, a narrower sampling frame of 6–7 year olds is believed to be more epidemiologically accurate and programmatically feasible to avoid larger sample sizes [16]. In school surveys, 6–7 year olds are approximated by 1st–2nd grade children. This approximation, however, proved ambiguous in countries where the target ages and grades did not effectively align. For example, in Ghana, children 8–10 years were frequent in 1st–2nd grade. In Malaysia and Indonesia, 1st–2nd grade typically corresponds to 7–8 year old children. Furthermore, some countries including Togo interpreted the guidelines as only including 6–7 year olds within 1st–2nd grade as the target population. Therefore, although the results show that 6–7 year old children still comprised the majority of all school surveys, the clarification of the age requirement in the TAS protocol is extremely important for planning and calculating an accurate survey design. To this end, the general guideline in the SSB tool has been revised for programs to specifically select the grade(s) in which 6–7 year old children are most likely to be found and then to use those grade(s) as the eligible target group for school surveys. This refined terminology was implemented successfully in the Vanuatu study and is likely to benefit and simplify future TAS implementations as well. Specimen Collection and Diagnostic Tests Specimen collection procedures were closely examined within the context of an operational research protocol that involved collecting blood into an EDTA-coated tube that would be transported and analyzed in a central laboratory, as opposed to directly conducting the ICT (or PanLF, Brugia Rapid) tests in the field. The perceived advantage of this method was to streamline blood collection in the field while being able to perform the diagnostic tests in a more controlled environment. This strategy proved adequate under operational research conditions to evaluate quality and consistency; however, it introduced logistic challenges in terms of transportation, time, and supplies. In addition, it was observed that field staff may be unfamiliar with drawing blood into EDTA tubes and basic pipetting techniques. This method was also more challenging for follow-up testing or where there was insufficient blood quantity or clotting. As a result, it may be more efficient programmatically for teams to conduct diagnostic tests in the field, directly transferring blood from the finger prick to the ICT or Brugia Rapid card with a calibrated capillary tube. This process was carried out successfully in Vanuatu, Indonesia, and Malaysia because of logistic restrictions that are likely to be duplicated in other TAS-eligible EUs. However, because the rapid diagnostic tests are extremely time sensitive and require good lighting, it is highly recommended that one team member be specifically assigned to timing and reading the tests in an area with sufficient lighting. However, in community surveys where house-to-house visits are more time consuming and on-the-spot diagnostic testing is likely to exacerbate this constraint, especially when surveys are conducted in the afternoon or evening, lighting becomes more restricted and it might be preferable to collect blood in EDTA tubes for later analysis. The performance and reliability of the diagnostic tests used for the TAS are undoubtedly critical to the success of the survey. In TAS-1, all positive ICT tests were immediately followed-up with a repeat test to confirm the initial finding. In all 33 positive cases, the original and repeat ICT tests were both positive, indicating 100% positive concordance. Despite this limited sample size, repeat ICT tests are deemed unnecessary under current TAS programmatic guidelines. More importantly, however, the field experiences here showed that the quality and consistency of ICT results can be strongly improved with robust training and strict adherence to reading the cards after exactly ten minutes. A newer filariasis test strip with potential greater sensitivity and reduced susceptibility to heat will only improve the accuracy of TAS results although it may require the adjustment of critical cutoff values and sample sizes [17]. Mf tests using blood smear (TAS-1 and TAS-2) and PCR methods (TAS-1 only) were examined in this study and showed that positive concordance to antigen (W. bancrofti) and antibody (Brugia spp.) results were comparable to previous studies, albeit with much smaller sample sizes [14]. Programmatically, however, the ICT and Brugia Rapid tests remain more suitable as the primary TAS diagnostic tool given their convenience advantages. Mf tests may best be utilized as a positive-case follow-up tool to test for potential hotspots, focal transmission, or spatial clustering. School versus Community-Based TAS in Targeted EUs The community-based TAS studies in Burkina Faso and Tanzania highlighted several specific challenges; in particular, both had trouble finding children in the daytime and poor census and map accuracy led to difficulties estimating the target age group, enumerating houses, and defining EA boundaries. While not especially pronounced in these studies, non-participation rates, cost, and time can all be reasonably assumed to be higher in community TAS than in school TAS. Of note, the number of field days for school surveys was heavily skewed by the considerable time taken in the Philippines due to severe weather and poor accessibility to insecure areas in the EU. Moreover, the level of planning, training, sensitization, and field effort required for the community-based surveys in Burkina Faso and Tanzania were qualitatively much higher as reported by field staff and supervisors. Perhaps if more community-based TAS were conducted in this study and if time included the planning stage and was measured in person-hours rather than days, differences between school and community-based surveys would have been more evident. Community-based TAS are also limited by having to often sample eligible children on evenings or weekends outside of regular school hours. A more critical assessment of the 75% enrolment rate requirement for TAS school surveys could, therefore, have important implications if this threshold could be justifiably lowered. A comparison of school and community-based TAS is also important to disprove any selection bias that may occur by only sampling school children, namely that those not attending school may also not be attending MDAs and are at a higher risk for infection. Preliminary results from separate TAS studies appear to suggest there is no statistically significant difference or change in the TAS-recommended outcome for EUs with school primary enrolment rates as low as 59% [18]. Although the majority of TAS EUs are still likely to qualify for school surveys, validation of such results would greatly streamline the overall efficiency of the TAS sampling strategy if school surveys could be used on a wider or exclusive basis. The composition of the TAS EU requires careful consideration to ensure that uniform epidemiological conditions persist across the EU. Despite the TAS being designed to provide an accurate EU-wide assessment, an EU that is smaller in area would presumably be more likely to include a self-sustaining subpopulation in its cluster sample (if such a ‘hotspot’ existed), but it might also be more cost prohibitive at a regional or national scale. In contrast, combining multiple IUs into one larger EU is more cost-effective, but clusters are spread more thinly across the EU and may miss potential hotspots where infection may persist in a focal area despite the overall EU successfully passing the TAS. A simple linear regression analysis of the EUs in this study showed moderate correlation between the cost of the TAS and EU area size, although cost is dependent on the geographical setting (e.g. transportation costs in Vanuatu were understandably greater than in Togo and Ghana despite relatively similar EU area sizes). The maximum limit of 2 million people for an EU also requires evidence; however, as the average EU population here was approximately 250,000 with a maximum of 682,000, no information about the validity of extremely large EU populations can be ascertained from this study. Identification of cost and epidemiological appropriateness of EUs may also be aided by spatial modeling or related research to determine additional criteria that is pertinent to defining an ideal EU size or cost for TAS. Although there was no evidence of major differences between rural and non-rural clusters in our study, MDA coverage and compliance might differ considerably in both areas. Likewise, cross-border infection with high-endemic neighboring IUs or other countries may increase the risk of transmission into the TAS EU. In the Dominican Republic study, some evidence of cross-border infection from Haitian immigrants was described in bordering EAs. Other high-risk factors could persist in specific parts of an EU but not others. In the Philippines, a census evaluation of 533 TAS-eligible children was conducted in a sub-area of the EU where there is a high concentration of certain axillary plants known to support breeding of LF vectors and increase inhabitants' risk of exposure and infection. Though no positive cases or significant difference from the rest of the EU was detected in the high-risk area (unpublished data), such factors should be carefully examined and accounted for when classifying TAS EUs in order to maintain a fairly homogeneous EU so far as risk of LF infection can be assessed. Post-MDA Surveillance TAS is currently recommended for EUs in post-MDA surveillance mode using an identical methodology to EUs evaluating the decision to stop or continue MDA. The results in this study support the reliability of this strategy but because TAS is not powered to detect change or designed to identify hotspots, post-MDA surveillance would best be complemented in the short and long term with other, complementary diagnostic tests and surveillance methods. In particular, antibody testing using Bm14, Bm33, or Wb123 assays may be highly suitable for post-MDA surveillance because it is more sensitive than antigen testing and may be superior to TAS for early detection of residual or resurgent LF infection. Initial findings from American Samoa and Haiti comparing filarial antigen and antibody responses seem to indicate that the antibody responses may be early markers of infection and not just exposure [19], [20]. The development of multiplex tools for NTD surveillance further facilitates the ability to conveniently examine several parameters at once [21], [22]. Xenomonitoring may also be a useful complementary post-MDA surveillance strategy because advances in molecular technology give it the potential to identify low-level LF infection in vector mosquitoes while being ‘non-invasive’ to the human population. Particularly in the majority of countries where filariasis is transmitted by Culex mosquitoes, efficient collection techniques exist and early results have been promising [23]–[25]. Furthermore, preliminary analysis of mosquitoes collected in American Samoa and Sri Lanka, in conjunction with these TAS studies, shows that xenomonitoring may provide comparable transmission markers and offer a cost-effective addition to the periodic post-MDA surveys where appropriately trained entomology teams are available (unpublished data). Longer term, post-TAS surveillance may also best be met through passive surveillance strategies using appropriate sentinel groups for routine blood monitoring or through malaria- or other disease-surveillance efforts [12], [22], [26]. Utilizing the antibody-based critical cutoff values for Brugia spp. EUs remains a concern for the current TAS protocol. While successfully passing the TAS based on more conservative thresholds increases the confidence of the results, the antibody-based thresholds may be overly restrictive, compared to the antigen-based thresholds for W. bancrofti. Additionally, the design effects calculated in the two Brugia spp. TAS (Indonesia and Malaysia) were notably higher than those assumed for calculating TAS sample sizes. In Malaysia, the large design effect can be partially attributed to a greater number of positive cases found in the EU than normally presumed by TAS. In Indonesia, however, the sample size and number of positive cases were similar to Burkina Faso yet the design effect was 2–3 times greater. Such findings may be indicative of inherent epidemiological differences of the respective EUs, but also warrant further investigation of the implications of evaluating filarial antigen and antibody using the same decision criteria. Interruption of ongoing LF transmission and cessation of MDA in an LF endemic area are milestone achievements but ones that require careful determination and accurate assessment. TAS guidelines are currently in place for stopping MDA and post-MDA surveillance and can be carried out effectively and efficiently with recommendations and best practices identified through the operational research experiences here. While the general sampling strategy has proven to be robust and pragmatic, thresholds and sample sizes may need to be modified as new diagnostic tools become available and validated. The ability of the TAS, however, to detect recent or ongoing LF transmission in hotspots within an EU that passes the critical threshold is still untested and requires longer-term empirical evidence. Additional research into the composition of EUs and mechanisms for hotspot detection and post-MDA surveillance will only help evolve and strengthen the current guidelines. From a broader perspective, the survey design principle of the TAS can be realistically applied and adapted to other NTDs as they reach similar points in their programs. The TAS may also provide a very opportune platform and sampling strategy to integrate assessments for co-endemic NTDs such as onchocerciasis and STH. Continued deployment and refinement of the TAS, therefore, is essential not only for LF elimination programs but potentially to the wider NTD community as well. Supporting Information Checklist S1 STROBE checklist. (DOC) Click here for additional data file.